Over 120,000 people suffer lower-extremity amputations each year in the United States, of which transfemoral (above-knee) amputations account for over 40%. Over 30,000 people in this transfemoral population require a new prosthetic limb each year—typically a passive, microprocessor-controlled knee joint, employing hydraulic damping and a passive carbon-fiber ankle-foot prosthesis. Such passive leg systems tend not to be biomimetic; instead they tend to be passive-elastic during stance and can neither perform net non-conservative work to propel the amputee upward and forward nor deliver the temporal torque response supplied by an intact knee and ankle joint during the gait cycle, and hence fail to fully restore function when integrated onto the residual limb. Researchers have hypothesized that the inability of conventional passive-elastic ankle-foot prostheses to provide sufficient positive power at terminal stance to limit heel strike losses of the adjacent leg is a key mechanism for the increased metabolic rate of walking amputees. These limitations in both ankle-foot and knee designs contribute to the severity of clinical problems experienced by transfemoral amputees.
Current leg prostheses tend not to provide the balance desired by the transfemoral community. Amputees often fall, especially while traversing rough or irregular terrain. This may be at least partially due because most ankle-foot prostheses fail to actively control a zero-moment point (ZMP) at the foot-ground interface, a balancing strategy sometimes employed in the field of humanoid robotics. In addition to balance problems, amputees tend to tire easier and walk slower than non-amputees. For example, amputees can require 10-60% more metabolic energy to walk than intact persons. The actual differences for any individual at a particular time result from differences in walking speed, physical fitness level, cause of amputation, level of amputation, and prosthetic intervention characteristics. Amputees may walk at much slower (e.g., 11-40%) self-selected gait speeds than do persons with intact limbs.
Integration of non-biomimetic ankle-foot and microprocessor-controlled knee prostheses has confounded researchers. Although some improvements in gait have been observed with variable-damper knee designs, many problems still remain for transfemoral amputees. For example, a variable-damper knee combined with a passive-elastic ankle-foot prosthesis offers little to no improvement in gait metabolism and walking speed compared to a mechanically-passive transfemoral system. Although some powered knee systems have been developed, these tend not to be biomechanically-conceived, and can take hours to fit and tune to a specific wearer. These powered knees tend to have a noisy motor and transmission system. Other powered robotic leg systems often exhibit three fundamental limitations: inefficient actuator design, non-biomimetic actuator control software, and poorly executed terrain-adaptation software. Without a biologically-conceived actuator, the motor must be made larger and heavier to deliver necessary joint powers.
To deliver the increased power, high gear-ratio transmissions are normally employed in powered leg prosthetic and orthotic applications, driven by high RPM brushless motors that are operated at currents in excess of 10× the rated current. The result is often a noisy transmission that dissipates battery power excessively, heating the motor windings instead of applying power to the joint. As a result, batteries must be made larger than necessary, or else the range on a battery charge is compromised unnecessarily. Further, motor heating can be excessive when extended periods of walking (e.g., hundreds of steps consecutively) are applied. The useful range of the prosthesis may be constrained by the need to “fold back” power when the motor windings get too hot. Most robots are programmed explicitly in a position-controlled or playback mode. Biophysically-conceived robots employ mono-articular and biarticular bionic muscle-tendon units that modulate joint impedance, equilibrium, torque and positive-feedback reflex during a gait cycle. The behavior of these bionic systems can be encoded in a relatively few parameters, implicitly defined rather than explicitly defined. Indeed, only a few parameters need to be changed to emulate biological behavior. In contrast, the explicitly controlled systems often require that movement as defined by joint angle trajectories is tuned to match biological behavior to create a response for every special case, driven by speed, terrain modality and wearer athleticism/payload. Even the most experienced clinicians may be unable to set up such a system. While many current robotic leg prostheses employ inertial componentry to estimate terrain modality, these are usually configured to adapt to the new terrain modality after several steps, whereas an intact person adjusts to terrain modality within each step. Though certain implementations of such a control may rely on playing back a temporal response at a particular terrain state, the desired behavior can be virtually impossible to tune.
It is therefore desirable to provide leg devices that provide a biomimetic response throughout a walking cycle.